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B0151
Title: Within, between, beyond: Methods for assessing variability in brain imaging Authors:  Michele Guindani - University of California, Irvine (United States) [presenting]
Abstract: An improved understanding of the heterogeneity of brain mechanisms is considered key for enabling the developments of targeted, precision, medicine interventions based on imaging features. We will describe a few Bayesian methods to characterize the heterogeneity typically observed both within- and between- subjects. First, we will describe models for multi-subject analysis that will identify population subgroups characterized by similar brain activity patterns, also by integrating available information on the subjects. Then, we will discuss methods to study changes in connectivity patterns over time, by combining analyses usually conducted through multiple steps into a single, unified, modeling framework that provides an accurate dynamic representation of brain processes. Finally, we will briefly address methods to characterize the association between a set of imaging as well as non-imaging predictors and an individual behavioral or clinical outcome. We will illustrate the performance of the methods in simulations and on real neuroimaging data.